Voice channels that carry digitized voice information can have distinctly different bit sequences even if they are of the same origin. Definite, reliable and rapid identification of such related (corresponding) voice channels is difficult particularly in communications networks, because the individual network elements of a communications network compress, encode and transmit the voice data with a delay that is sometimes large and variable.
Locating those signals that come from the same origin is suited to applications in telecommunications networks in which internal interfaces are routed over transmission channels whose bandwidth requirements needs to be reduced. Such a use is described, for example, in the German application filed under reference “10 2006 060 002.9” dated Dec. 19, 2006, and not previously published. These applications make it possible to operate communications networks more efficiently, because communications paths may be shortened if applicable, and at the same time the bandwidth requirement needed for signal transmission on certain sections of communications networks can be reduced.
Various mathematical techniques are available for solving this problem of identifying signals of the same origin. Suitable methods include both “correlation analysis” (described in chapter 13.5, Stearns, S. D.; “Digital processing of analog signals”; Oldenbourg, München & Wien 1984) and “system analysis” (described in chapter 9, “Adaptive Signal Processing”; Widrow, B.; Stearns, S. D.; Prentice-Hall, Englewood Cliffs, N.J., 1985). Both methods have in common the fact that they supply unreliable conclusions in situations in which two non-corresponding channels are similar, or the signal levels of the channels are low. For both “correlation analysis” and “system analysis”, large amounts of computing power and long analysis times are needed to rectify this shortcoming in order to use either of these techniques in practice.